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1000
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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Purpose</jats:title>
<jats:p>The present study explores the dynamics of cell death in Hirschsprung’s disease (HSCR) and control (CO) groups under inflammatory stress conditions.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>Using flow cytometry, we analyzed intestinal colonic organoid cultures derived from the ganglionic segment of the HSCR and CO groups. Our analysis focused on the quantification of RIPK1-independent and RIPK1-dependent apoptosis, as well as necroptosis in both viable and non-viable cells under acute and chronic inflammatory stress.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>Our findings indicate that HSCR cells are particularly vulnerable to inflammation during acute proinflammatory stress, as evidenced by an increase in dead cells (Zombie +). Under chronic conditions, adaptive changes are observed in both HSCR and CO groups, indicating survival mechanisms. These adaptations are uniquely altered in HSCR, suggesting an impaired response to chronic inflammation. HSCR cells show significantly decreased RIPK1-dependent apoptosis in acute scenarios compared to chronic ones, unlike the CO group, implying varied responses to different inflammatory stresses. In non-viable cells, considerable changes in RIPK1-dependent apoptosis under chronic conditions in HSCR indicate a heightened inflammatory response compared to CO.</jats:p>
</jats:sec><jats:sec>
<jats:title>Conclusion</jats:title>
<jats:p>This research provides insights into cell death regulation in HSCR under inflammatory stress by using patient-derived organoids, underscoring the complexity of its inflammatory response.</jats:p>
</jats:sec>
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1000
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Hinweis
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DeepGreen-ID: eeddd2ce11ff4b1e95ddd0a8aae44074 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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